On the Interplay Between Resource-Management Overhead and Performance in Sensor Networks: An Information Theoretic Approach

Resource management (RM) is a critical action in systems with limited resources such as sensor networks. Efficient RM depends heavily upon the availability of accurate information on the state of available resources. However, exchange of state information incurs an overhead on the system. In this paper, the sensing and computing resource management in sensor networks is considered. A lossless, distributed source-coding framework is presented to model the exchange of state information. The framework enables the characterization of the interplay between the performance and overhead of RM by leveraging the correlation among the state information of various nodes. Moreover, the proposed framework enables an improved estimate of the lower bound for the minimum control overhead necessary to accurately describe the state of nodes in the network. This improvement is achieved by exploiting the correlation among the state information of nodes as well as the available information on prior resource allocation actions as side information.